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  1. null (Ed.)
    ABSTRACT Separating galactic foreground emission from maps of the cosmic microwave background (CMB) and quantifying the uncertainty in the CMB maps due to errors in foreground separation are important for avoiding biases in scientific conclusions. Our ability to quantify such uncertainty is limited by our lack of a model for the statistical distribution of the foreground emission. Here, we use a deep convolutional generative adversarial network (DCGAN) to create an effective non-Gaussian statistical model for intensity of emission by interstellar dust. For training data we use a set of dust maps inferred from observations by the Planck satellite. A DCGAN is uniquely suited for such unsupervised learning tasks as it can learn to model a complex non-Gaussian distribution directly from examples. We then use these simulations to train a second neural network to estimate the underlying CMB signal from dust-contaminated maps. We discuss other potential uses for the trained DCGAN, and the generalization to polarized emission from both dust and synchrotron. 
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  2. Abstract

    We show the improvement to cosmological constraints from galaxy cluster surveys with the addition of cosmic microwave background (CMB)-cluster lensing data. We explore the cosmological implications of adding mass information from the 3.1σdetection of gravitational lensing of the CMB by galaxy clusters to the Sunyaev–Zel’dovich (SZ) selected galaxy cluster sample from the 2500 deg2SPT-SZ survey and targeted optical and X-ray follow-up data. In the ΛCDM model, the combination of the cluster sample with the Planck power spectrum measurements prefersσ8Ωm/0.30.5=0.831±0.020. Adding the cluster data reduces the uncertainty on this quantity by a factor of 1.4, which is unchanged whether the 3.1σCMB-cluster lensing measurement is included or not. We then forecast the impact of CMB-cluster lensing measurements with future cluster catalogs. Adding CMB-cluster lensing measurements to the SZ cluster catalog of the ongoing SPT-3G survey is expected to improve the expected constraint on the dark energy equation of statewby a factor of 1.3 toσ(w) = 0.19. We find the largest improvements from CMB-cluster lensing measurements to be forσ8, where adding CMB-cluster lensing data to the cluster number counts reduces the expected uncertainty onσ8by respective factors of 2.4 and 3.6 for SPT-3G and CMB-S4.

     
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  3. Abstract

    SPT-3G is the third survey receiver operating on the South Pole Telescope dedicated to high-resolution observations of the cosmic microwave background (CMB). Sensitive measurements of the temperature and polarization anisotropies of the CMB provide a powerful data set for constraining cosmology. Additionally, CMB surveys with arcminute-scale resolution are capable of detecting galaxy clusters, millimeter-wave bright galaxies, and a variety of transient phenomena. The SPT-3G instrument provides a significant improvement in mapping speed over its predecessors, SPT-SZ and SPTpol. The broadband optics design of the instrument achieves a 430 mm diameter image plane across observing bands of 95, 150, and 220 GHz, with 1.2′ FWHM beam response at 150 GHz. In the receiver, this image plane is populated with 2690 dual-polarization, trichroic pixels (∼16,000 detectors) read out using a 68× digital frequency-domain multiplexing readout system. In 2018, SPT-3G began a multiyear survey of 1500 deg2of the southern sky. We summarize the unique optical, cryogenic, detector, and readout technologies employed in SPT-3G, and we report on the integrated performance of the instrument.

     
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